What are the state-of-the-art results in OpenAI's gym environments?
There is the leaderboard page at the gym GitHub repository that contains links to specific implementations that &quot;solve&quot; the different gym environments, where &quot;to solve&quot; means &quot;to reach a certain level of performance&quot;, which, given a fixed reward function, is typically measured as the average (episodic) return/reward. For example, in the case of the CartPole environment, you solve it when you get an average reward of $195.0$ over $100$ consecutive trials.